Data Warehousing big data
big data | report | project | assignment代做 – 这是利用big data进行训练的代写, 对big data的流程进行训练解析, 是比较有代表性的big data/report等代写方向, 这个项目是assignment代写的代写题目
La Trobe Business School
BUS5WB – Data Warehousing and big data assignment 0 2 : OLAP, Cubes, and Insights Marks: 4 0% Assignment Type: Individual Release Date: Thursday 05 May 2022 Due Date: 5 : 00 PM Tuesday 31 May 2022
The second assignment focuses on the agility of data warehouse developments, redesigning an existing dimensional model, and the use SSDT tools and techniques to generate business insights.
Your ability to correctly apply these tools to a business use case will be assessed.
Task 1: Agile data warehouse development approach Conduct a critical evaluation of the dimensional models that you designed in assignment 01 and formulate an agile development approach to build out a corresponding data warehouse. The lecture on data warehouse lifecycle provides a basis for this formulation but you are required to reference external reading on agile and cloud data warehouse solutions (preferably Azure) to determine the critical components that will address the business needs with agile delivery.
The following business case applies to Tasks 2 and 3: The CIO of Valeur , a large national supermarket/retail store chain has recently introduced a loyalty card program and keen to gain a more comprehensive understanding of the organisations customer base through traditional transactional data as well as the newer and effective demographic analysis techniques. The customer relationship management (CRM) team working under her supervision have already put together a summarised data warehouse containing some transaction data and customer demographics. Although the data is accurate and complete, the CIO believes the structure is not. She feels theres more information that can be captured by the warehouse. She has two main business problems in mind. Firstly, improving the current dimensional model/ warehouse to capture all relevant information that applies to customers, such as demographics. Secondly, using current data in the warehouse to better understand the customer base by identifying customer behaviours and thereby potential sales and marketing opportunities.
Task 2: Dimensional model redesign Study the given dimensional model to determine what is lacking in response to the business need. Identify potential improvements to the dimensional model. This can be in the form of new attributes, new dimensions, new measures or the use of dimension design techniques. Present your recommendations with supporting evidence and the new dimensional model.
Task 3: Demonstration of Analysis Tools The data warehouse ( ValeurDW ) is accessible from the WB server.
Use the knowledge and experience gained from tutorials 7-10, to demonstrate each of the seven analysis technique/tool – 1) SSAS, 2 ) Cube Features, 3 ) SSRS, 4 ) MDX, 5 ) SSDT Data mining, 6 ) Excel Power Pivot, and 7 ) PowerBI, by conducting a comprehensive analysis of customer behaviours and thereby potential sales and marketing opportunities.
It is anticipated that you will demonstrate your proficiency with advanced analysis approaches rather than simple and straightforward querying. Each demonstration should lead towards an insight/recommendation of business value. A minimum of seven demonstrations is expected, preferably in increasing complexity and increasing decision value.
La Trobe Business School
Deliverables
A report on the three tasks.
- The report should be compiled in Microsoft Word only, font size 11.
- Should not exceed 20 pages., including diagrams, tables and any other visualisations/ screen captures.
- Contain a reference to project files (noting project file names) on the server.
- Make realistic assumptions on any information (schema or business requirements) that may be
missing in the above description. Discuss all assumptions in the report.
Dimensional Model
DimTransactionDate
TransactionDateKey
TransactionDate
Day
Month
Quarter
Year
DimProductCategory
ProductCategoryKey
ProductCategoryID
CategoryName
FactTransactionSummary
CustomerKey
ProductCategoryKey
FeedbackKey
TransactionDateKey
TotalQuantity
TotalSale
DimFeedback
FeedbackKey
FeedbackID
FeedbackService
FeedbackPrice
FeedbackVariety
FeedbackValue
DimCustomer
CustomerKey
CustomerID
Age
Gender
Education
SuburbProfile
CreditRanking
La Trobe Business School
Rubric
Criteria P C B A
Agile data warehouse
development
approach
7 marks
Limited to no
agile elements
in the
proposed
approach
Some use of
agile elements
in the proposed
approach
A coherent
approach that
considers all agile
elements
A complete agile
approach with
detailed
description of
each element
Dimensional model
redesign
8 marks
A minimal
attempt at
improving the
dimensional
model.
A basic attempt
at improving the
dimensional
model.
A complete
attempt at
improving the
dimensional model.
A complete
attempt at
improving the
dimensional
model with
precision focus on
integrating
transaction data,
and all aspects of
demographics.
Demonstration of
analysis tools
25 marks
(3 marks * 7 tools)
4 marks - increasing
complexity and
increasing decision-
making value
Simple
demonstration
of tools and
techniques
with
rudimentary
insights.
Standard
demonstration
of tools and
techniques with
basic insights.
A good
demonstration all
of tools and
techniques with
relevant insights.
A complete
demonstration all
of tools and
techniques with
insights of
increasing
decision-making
value.